Jobs at Tempo Software

Design, develop, deploy, and maintain cloud-native full-stack features and APIs. Improve performance, reliability, and security; write tests; debug production issues; collaborate with product, SRE, QA, and support teams; use AI-assisted coding tools to accelerate delivery.

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

Lead and scale Tempo's Product Operations by building operating cadence, tooling, AI-driven workflows, dashboards, and enablement programs. Partner with CPO and cross-functional leaders to align strategy, roadmap, capacity, and customer insights to improve product delivery and outcomes.

Own product strategy and roadmap for Tempo Financial Manager's budgeting, cost, and billing features. Lead discovery with CFOs and FP&A leaders, design scenario modeling and continuous forecasting, and connect portfolio decisions to financial plans. Partner closely with engineering, design, and integrations teams to link Jira, capacity, and timesheet data to budgets, forecasts, and earned-value metrics, and drive ERP integrations (SAP/Oracle/Workday).

The Vice President of AI will define and lead the AI strategy at Tempo, integrating AI capabilities into products, building teams, and ensuring ethical use of AI while driving business outcomes and customer value.

Build end-to-end automation and AI agents across identity, endpoint, SaaS, and ITSM systems. Automate onboarding/offboarding, ticket triage, self-service flows, and integrations. Operate and govern Vertex AI agents, establish KPIs, mentor sysadmins, and maintain reliable, auditable automations with security and compliance controls.

The GTM Engineer will build AI systems for revenue generation, design data pipelines, and integrate automation architecture to enhance marketing and sales operations.

The Senior AI/ML Engineer will develop AI systems for enterprise decision-making, focusing on LLMs and real-time data processing. Responsibilities include building detection systems, insight engines, evaluation frameworks, and collaborating with engineers to ensure robust AI product engineering.